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The source code of the implementations and the tuning of parameters is discussed below. Please consider two important factors while we discuss the parameters tuning: a) We define an anomalous event as one which significantly varies from the normal behaviour of the Internet Path and the perturbation persists for at least three hours. b) The measurements made by IEPM-BW are at least 45 mins apart.
Fig. 2: ROC curves for Plateau (PL), |
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a) Plateau Algorithm
The Plateau Algorithm takes four input parameters - history buffer length, trigger buffer length, sensitivity and threshold. We define the trigger buffer length to hold observations spanning at least 3 hours (since we define an anomalous event as one that persists for at least 3 hours). Since the measurements made by IEPM are 45 mins apart, we get about 6 observations. We then empirically determine the optimal length of the history buffer to span at least 5 days ~ 240 observations.
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The source code of the implementation is available in [C#|http://www.slac.stanford.edu/~kalim/event-detection/published-src/c-plateau-impl.html] \[[cs|http://www.slac.stanford.edu/~kalim/event-detection/published-src/plateau.cs]\] and [perl|http://www.slac.stanford.edu/~kalim/event-detection/published-src/plateau.pl.html] \[[pl|http://www.slac.stanford.edu/~kalim/event-detection/published-src/plateau.pl]\] |
b) Adaptive Fault Detection
Adaptive Fault Detection
c) Kalman Filters
Kalman Filters
d) Decision Theoretic Approach
Decision Theoretic Approach
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([utilityFunctions|http://www.slac.stanford.edu/~kalim/event-detection/published-src/utilityFunctions.pm.html] \[[pm|http://www.slac.stanford.edu/~kalim/event-detection/published-src/utilityFunctions.pm]\]). |
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